Instructions to use connectivity/bert_ft_qqp-27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-27 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-27")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-27") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-27", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-27: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-27/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-27/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-27/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- b4cf3289b7fb5645937c907726464884e9c74c5bde8763ca810b4bf83bdeffda
- Size of remote file:
- 438 MB
- SHA256:
- 7430f9a573fb03114b2248cf40a61ad0f5bd5247b3699341d480e15176b5e155
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